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chore: Adding telemetry for the dataset metadata. This one is specially for … #1917
chore: Adding telemetry for the dataset metadata. This one is specially for … #1917
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…adding count of the columns.
Hey @saileshbaidya 👋! We use semantic commit messages to streamline the release process. Examples of commit messages with semantic prefixes:
To test your commit locally, please follow our guild on building from source. |
/azp run |
Commenter does not have sufficient privileges for PR 1917 in repo microsoft/SynapseML |
/azp run |
Azure Pipelines successfully started running 1 pipeline(s). |
…eshbaidya/SynapseML_SB into saibai/TelemetryTask1893417
/azp run |
Azure Pipelines successfully started running 1 pipeline(s). |
Codecov Report
@@ Coverage Diff @@
## master #1917 +/- ##
==========================================
+ Coverage 86.77% 86.81% +0.03%
==========================================
Files 301 301
Lines 15677 15783 +106
Branches 815 848 +33
==========================================
+ Hits 13604 13702 +98
- Misses 2073 2081 +8
... and 1 file with indirect coverage changes Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here. |
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Azure Pipelines successfully started running 1 pipeline(s). |
@@ -12,10 +12,11 @@ import scala.collection.mutable | |||
case class SynapseMLLogInfo(uid: String, | |||
className: String, | |||
method: String, | |||
buildVersion: String) | |||
buildVersion: String, | |||
columns: Int = -1) |
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In scala we use Option types to denote something that can be there or not. You can add this without changing much by also adding a different "this" method so you can just pass in columns as a non-optioned int too
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Will do. Agree, better to use language features.
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I have sent out new iteration with the changes @mhamilton723.
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Minor nit on the argument type of columns, should be Option[Int] instead of Int
def logFit[T](f: => T, columns: Int = -1): T = { | ||
logVerb("fit", f, columns) | ||
} | ||
|
||
def logTrain[T](f: => T): T = { | ||
logVerb("train", f) | ||
def logTrain[T](f: => T, columns: Int = -1): T = { | ||
logVerb("train", f, columns) | ||
} | ||
|
||
def logTransform[T](f: => T): T = { | ||
logVerb("transform", f) | ||
def logTransform[T](f: => T, columns: Int = -1): T = { | ||
logVerb("transform", f, columns) | ||
} |
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Unfortunately we still should probabbly get rid of this -1 default arg here. Please remove the default arg from this function as it should be provided in all cases right?
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Did that. Please check.
protected def logBase(methodName: String, columns:Int = -1): Unit = { | ||
logBase(SynapseMLLogInfo( | ||
uid, | ||
getClass.toString, | ||
methodName, | ||
BuildInfo.version, | ||
if (columns == -1) None else Some(columns))) |
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Maybe this can just take in an Option of int too because it isnt used much
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Did that. Please check.
…eshbaidya/SynapseML_SB into saibai/TelemetryTask1893417
/azp run |
Azure Pipelines successfully started running 1 pipeline(s). |
…for a log api logBase call
/azp run |
Azure Pipelines successfully started running 1 pipeline(s). |
…adding count of the columns.
Related Issues/PRs
Task: 2348953
Close #2348953
What changes are proposed in this pull request?
Adding the dataset schema column count to the existing logs.
Briefly describe the changes included in this Pull Request.
How is this patch tested?
I am going to run the existing tests that calls the logging apis.
Does this PR change any dependencies?
Does this PR add a new feature? If so, have you added samples on website?
website/docs/documentation
folder.Make sure you choose the correct class
estimators/transformers
and namespace.DocTable
points to correct API link.yarn run start
to make sure the website renders correctly.<!--pytest-codeblocks:cont-->
before each python code blocks to enable auto-tests for python samples.WebsiteSamplesTests
job pass in the pipeline.